Automatic FIR Generation System Using NLP and Machine Learning

ABSTRACTII. This paper presents the design and development ofan AI-based FIR Assistant that automates theidentification of relevant Indian Penal Code (IPC)sections from written complaint descriptions. Thesystem integrates Natural Language Processing(NLP) techniques with a MERN stack(MongoDB, Express, React, Node.js) webinterface to simplify FIR documentation for policepersonnel.III. The backend uses Python-based NLP modulessuch as tokenization, Named Entity Recognition(NER), and crime-intent classification to extractmeaningful information from complaint text. Theextracted features are matched with an IPCknowledge base using hybrid logic consisting ofrule-based mapping and machine-learning–supported similarity scoring. The MERN-basedfrontend enables officers to input complaints,view recommended IPC sections, and generate astructured FIR automatically.IV. This work demonstrates that NLP-assisted legalclassification significantly reduces manual errors,improves documentation speed, and enhancesaccuracy in FIR preparation, enabling moreefficient policing and digital governance.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-09
DOI
https://doi.org/10.5281/zenodo.20609756
Primary Topic
Artificial Intelligence in Law
Type
article
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article

Automatic FIR Generation System Using NLP and Machine Learning

Mrs. G.A. Muthuchelvi, Nithya T, Divya S
Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Law
article

Automatic FIR Generation System Using NLP and Machine Learning

Mrs. G.A. Muthuchelvi, Nithya T, Divya S
article en

Abstract

ABSTRACTII. This paper presents the design and development ofan AI-based FIR Assistant that automates theidentification of relevant Indian Penal Code (IPC)sections from written complaint descriptions. Thesystem integrates Natural Language Processing(NLP) techniques with a MERN stack(MongoDB, Express, React, Node.js) webinterface to simplify FIR documentation for policepersonnel.III. The backend uses Python-based NLP modulessuch as tokenization, Named Entity Recognition(NER), and crime-intent classification to extractmeaningful information from complaint text. Theextracted features are matched with an IPCknowledge base using hybrid logic consisting ofrule-based mapping and machine-learning–supported similarity scoring. The MERN-basedfrontend enables officers to input complaints,view recommended IPC sections, and generate astructured FIR automatically.IV. This work demonstrates that NLP-assisted legalclassification significantly reduces manual errors,improves documentation speed, and enhancesaccuracy in FIR preparation, enabling moreefficient policing and digital governance.

Zenodo (CERN European Organization for Nuclear Research)
Madurai Kamaraj University (IN)
Peace, Justice and strong institutions
Openalex Percentile: Top 3%
Artificial Intelligence in Law
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Automatic FIR Generation System Using NLP and Machine Learning — Mrs. G.A. Muthuchelvi, Nithya T, Divya S · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS